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This study focuses on the estimation of the Emax dose-response model, a widely utilized framework in clinical trials, agriculture, and environmental experiments. Existing challenges in obtaining maximum likelihood estimates (MLE) for model…

Methodology · Statistics 2025-06-11 Giacomo Aletti , Nancy Flournoy , Caterina May , Chiara Tommasi

In this paper, the maximum L$q$-likelihood estimator (ML$q$E), a new parameter estimator based on nonextensive entropy [Kibernetika 3 (1967) 30--35] is introduced. The properties of the ML$q$E are studied via asymptotic analysis and…

Statistics Theory · Mathematics 2010-02-25 Davide Ferrari , Yuhong Yang

We study the asymptotic properties of nearest-neighbor random walks in 1d random environment under the influence of an external field of intensity $\lambda\in\mathbb{R}$. For ergodic shift-invariant environments, we show that the limiting…

Probability · Mathematics 2018-06-11 Alessandra Faggionato , Michele Salvi

We describe Monte Carlo approximation to the maximum likelihood estimator in models with intractable norming constants and explanatory variables. We consider both sources of randomness (due to the initial sample and to Monte Carlo…

Methodology · Statistics 2016-12-08 Blazej Miasojedow , Wojciech Niemiro , Jan Palczewski , Wojciech Rejchel

In this article we investigate consistency and asymptotic normality of the maximum likelihood and the posterior distribution of the parameters in the context of state space stochastic differential equations (SDEs). We then extend our…

Statistics Theory · Mathematics 2018-11-13 Trisha Maitra , Sourabh Bhattacharya

We apply the techniques of stochastic integration with respect to fractional Brownian motion and the theory of regularity and supremum estimation for stochastic processes to study the maximum likelihood estimator (MLE) for the drift…

Statistics Theory · Mathematics 2007-08-22 Ciprian A. Tudor , Frederi G. Viens

Andresen and Spokoiny's (2013) ``critical dimension in semiparametric estimation`` provide a technique for the finite sample analysis of profile M-estimators. This paper uses very similar ideas to derive two convergence results for the…

Statistics Theory · Mathematics 2015-01-08 Andreas Andresen , Vladimir Spokoiny

The parametric maximum likelihood estimation problem is addressed in the context of quantum walk theory for quantum walks on the lattice of integers. A coin action is presented, with the real parameter $\theta$ to be estimated identified…

Quantum Physics · Physics 2023-05-31 Demosthenes Ellinas , Peter D. Jarvis , Matthew Pearce

We study the distribution of the maximum $M$ of a random walk whose increments have a distribution with negative mean and belonging, for some $\gamma>0$, to a subclass of the class $\mathcal{S}_\gamma$--see, for example, Chover, Ney, and…

Probability · Mathematics 2017-11-29 Stan Zachary , Sergey Foss

This paper extends some prominent statistical results including \emph{Fisher Theorem and Wilks phenomenon} to the penalized maximum likelihood estimation with a quadratic penalization. It appears that sharp expansions for the penalized MLE…

Methodology · Statistics 2015-08-11 Vladimir Spokoiny

Consider semiparametric models that display local asymptotic exponentiality (Ibragimov and Has'minskii (1981)), an asymptotic property of the likelihood associated with discontinuities of densities. Our interest goes to estimation of the…

Statistics Theory · Mathematics 2013-12-19 Bas Kleijn , Bartek Knapik

We consider the classical estimation problem of an unknown drift parameter within classes of nondegenerate diffusion processes. Using rough path theory (in the sense of T. Lyons), we analyze the Maximum Likelihood Estimator (MLE) with…

Probability · Mathematics 2016-09-29 Joscha Diehl , Peter Friz , Hilmar Mai

The H\"usler-Reiss distribution describes the limit of the pointwise maxima of a bivariate normal distribution. This distribution is defined by a single parameter, $\lambda$. We provide asymptotic theory for maximum likelihood estimation of…

Statistics Theory · Mathematics 2024-10-16 Hank Flury , Jan Hannig , Richard Smith

In cluster-specific studies, ordinary logistic regression and conditional logistic regression for binary outcomes provide maximum likelihood estimator (MLE) and conditional maximum likelihood estimator (CMLE), respectively. In this paper,…

Statistics Theory · Mathematics 2020-05-14 Zhulin He , Yuyuan Ouyang

We study one-dimensional nearest neighbour random walk in site-random environment. We establish precise (sharp) large deviations in the so-called ballistic regime, when the random walk drifts to the right with linear speed. In the…

Probability · Mathematics 2018-01-08 Dariusz Buraczewski , Piotr Dyszewski

We study the asymptotic behaviour of random walks in i.i.d. non-elliptic random environments on $\mathbb{Z}^d$. Standard conditions (and proofs) for ballisticity and the central limit theorem require ellipticity. We use oriented percolation…

Probability · Mathematics 2018-11-27 Mark Holmes , Thomas S. Salisbury

In order to learn the complex features of large spatio-temporal data, models with large parameter sets are often required. However, estimating a large number of parameters is often infeasible due to the computational and memory costs of…

Computation · Statistics 2018-07-02 Matthew Edwards , Stefano Castruccio , Dorit Hammerling

We study nonparametric estimation of the sub-distribution functions for current status data with competing risks. Our main interest is in the nonparametric maximum likelihood estimator (MLE), and for comparison we also consider a simpler…

Statistics Theory · Mathematics 2008-06-20 Piet Groeneboom , Marloes H. Maathuis , Jon A. Wellner

The Rasch model has been widely used to analyse item response data in psychometrics and educational assessments. When the number of individuals and items are large, it may be impractical to provide all possible responses. It is desirable to…

Statistics Theory · Mathematics 2025-01-15 Pai Peng , Lianqiang Qu , Qiuping Wang , Shufang Wang , Ting Yan

An autoregressive process with Markov regime is an autoregressive process for which the regression function at each time point is given by a nonobservable Markov chain. In this paper we consider the asymptotic properties of the maximum…

Statistics Theory · Mathematics 2007-06-13 Randal Douc , Eric Moulines , Tobias Ryden